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Research has shown the effectiveness of reasoning (e.g., Chain-of-Thought), planning (e.g., SelfAsk), and retrieval augmented generation strategies to improve the performance of Large Language Models (LLMs) on various tasks, such as question answering. However, using a single fixed strategy to answer different kinds of questions is suboptimal in performance and inefficient in terms of generated output tokens and performed retrievals. In our work, we propose a novel technique DyPlan, to induce a dynamic strategy selection process in LLMs, to improve performance and reduce costs in question-answering. DyPlan incorporates an initial decision step to select the most suitable strategy conditioned on the input question and guides the LLM's response generation accordingly. We extend DyPlan to DyPlan-verify, adding an internal verification and correction process to further enrich the generated answer. Experiments on three prominent multi-hop question answering (MHQA) datasets reveal how DyPlan can improve model performance by 7-13% while reducing the cost by 11-32% relative to the best baseline model., Comment: Under review at ACL Rolling Review

Layered transition metal dichalcogenides (TMDs) stabilize in multiple structural forms with profoundly distinct and exotic electronic phases. Interfacing different layer types is a promising route to manipulate TMDs' properties, not only as a means to engineer quantum devices, but also as a route to explore fundamental physics in complex matter. Here we use angle-resolved photoemission (ARPES) to investigate a strong layering-dependent enhancement of superconductivity in TaS$_2$, in which the superconducting transition temperature, $T_c$, of its $2H$ structural phase is nearly tripled when insulating $1T$ layers are inserted into the system. The study is facilitated by a novel vanadium-intercalation approach to synthesizing various TaS$_2$ polytypes, which improves the quality of ARPES data while leaving key aspects of the electronic structure and properties intact. The spectra show the clear opening of the charge density wave gap in the pure $2H$ phase and its suppression when $1T$ layers are introduced to the system. Moreover, in the mixed-layer $4Hb$ system, we observe a strongly momentum-anisotropic increase in electron-phonon coupling near the Fermi level relative to the $2H$ phase. Both phenomena help to account for the increased $T_c$ in mixed $2H$/$1T$ layer structures.

The CHIPS R&D project focuses on development of low-cost water Cherenkov neutrino detectors through novel design strategies and resourceful engineering. This work presents an end-to-end DAQ solution intended for a recent 5 kt CHIPS prototype, which is largely based on affordable mass-produced components. Much like the detector itself, the presented instrumentation is composed of modular arrays that can be scaled up and easily serviced. A single such array can carry up to 30 photomultiplier tubes (PMTs) accompanied by electronics that generate high voltage in-situ and deliver time resolution of up to 0.69 ns. In addition, the technology is compatible with the White Rabbit timing system, which can synchronize its elements to within 100 ps. While deployment issues did not permit the presented DAQ system to operate beyond initial evaluation, the presented hardware and software successfully passed numerous commissioning tests that demonstrated their viability for use in a large-scale neutrino detector, instrumented with thousands of PMTs., Comment: 30 pages, 28 figures, submitted to MDPI Applied Sciences, Special Issue: Advanced Neutrino Detector Development and Application

Bipolaronic superconductivity is an exotic pairing mechanism proposed for materials like Ba$_{1-x}$K$_x$BiO$_3$ (BKBO); however, conclusive experimental evidence for a (bi)polaron metallic state in this material remains elusive. Here, we combine resonant inelastic x-ray and neutron total scattering techniques with advanced modelling to study the local lattice distortions, electronic structure, and electron-phonon coupling ($e$-ph) in BKBO as a function of doping. Data for the parent compound ($x = 0$) indicates that the electronic gap opens in predominantly oxygen-derived states strongly coupled to a long-range ordered breathing distortion of the oxygen sublattice. Upon doping, short-range breathing distortions and sizable ($e$-ph) coupling persist into the superconducting regime ($x = 0.4$). Comparisons with exact diagonalization and determinant quantum Monte Carlo calculations further support this conclusion. Our results provide compelling evidence that BKBO's metallic phase hosts a liquid of small (bi)polarons derived from local breathing distortions of the lattice, with implications for understanding the low-temperature superconducting instability

The application of metal oxide nanomaterials (MOx NMs) in the agrifood industry offers innovative solutions that can facilitate a paradigm shift in a sector that is currently facing challenges in meeting the growing requirements for food production, while safeguarding the environment from the impacts of current agriculture practices. This review comprehensively illustrates recent advancements and applications of MOx for sustainable practices in the food and agricultural industries and environmental preservation. Relevant published data point out that MOx NMs can be tailored for specific properties, enabling advanced design concepts with improved features for various applications in the agrifood industry. Applications include nano-agrochemical formulation, control of food quality through nanosensors, and smart food packaging. Furthermore, recent research suggests MOx's vital role in addressing environmental challenges by removing toxic elements from contaminated soil and water. This mitigates the environmental effects of widespread agrichemical use and creates a more favorable environment for plant growth. The review also discusses potential barriers, particularly regarding MOx toxicity and risk evaluation. Fundamental concerns about possible adverse effects on human health and the environment must be addressed to establish an appropriate regulatory framework for nano metal oxide-based food and agricultural products.

Progressing beyond centralized AI is of paramount importance, yet, distributed AI solutions, in particular various federated learning (FL) algorithms, are often not comprehensively assessed, which prevents the research community from identifying the most promising approaches and practitioners from being convinced that a certain solution is deployment-ready. The largest hurdle towards FL algorithm evaluation is the difficulty of conducting real-world experiments over a variety of FL client devices and different platforms, with different datasets and data distribution, all while assessing various dimensions of algorithm performance, such as inference accuracy, energy consumption, and time to convergence, to name a few. In this paper, we present CoLExT, a real-world testbed for FL research. CoLExT is designed to streamline experimentation with custom FL algorithms in a rich testbed configuration space, with a large number of heterogeneous edge devices, ranging from single-board computers to smartphones, and provides real-time collection and visualization of a variety of metrics through automatic instrumentation. According to our evaluation, porting FL algorithms to CoLExT requires minimal involvement from the developer, and the instrumentation introduces minimal resource usage overhead. Furthermore, through an initial investigation involving popular FL algorithms running on CoLExT, we reveal previously unknown trade-offs, inefficiencies, and programming bugs.

Two-dimensional electron liquids (2DELs) have increasing technological relevance for ultrafast electronics and spintronics, yet significant gaps in their fundamental understanding are exemplified on the prototypical SrTiO$_3$. We correlate the exact SrTiO$_3$(001) surface structure with distinct 2DELs through combined microscopic angle-resolved photoemission spectroscopy and non-contact atomic force microscopy on truly bulk-terminated surfaces that alleviate structural uncertainties inherent to this long-studied system. The SrO termination is shown to develop a 2DEL following the creation of oxygen vacancies, unlike the intrinsically metallic TiO$_2$ termination. Differences in degeneracy of the 2DELs, that share the same band filling and identical band bending, are assigned to polar distortions of the Ti atoms in combination with spin order, supported with the extraction of fundamental electron-phonon coupling strength. These results not only resolve the ambiguities regarding 2DELs on SrTiO$_3$ thus far, but also pave the way to manipulating band filling and spin order in oxide 2DELs in general.

Strongly-correlated transition-metal oxides are widely known for their various exotic phenomena. This is exemplified by rare-earth nickelates such as LaNiO$_{3}$, which possess intimate interconnections between their electronic, spin, and lattice degrees of freedom. Their properties can be further enhanced by pairing them in hybrid heterostructures, which can lead to hidden phases and emergent phenomena. An important example is the LaNiO$_{3}$/LaTiO$_{3}$ superlattice, where an interlayer electron transfer has been observed from LaTiO$_{3}$ into LaNiO$_{3}$ leading to a high-spin state. However, macroscopic emergence of magnetic order associated with this high-spin state has so far not been observed. Here, by using muon spin rotation, x-ray absorption, and resonant inelastic x-ray scattering, we present direct evidence of an emergent antiferromagnetic order with high magnon energy and exchange interactions at the LaNiO$_{3}$/LaTiO$_{3}$ interface. As the magnetism is purely interfacial, a single LaNiO$_{3}$/LaTiO$_{3}$ interface can essentially behave as an atomically thin strongly-correlated quasi-two-dimensional antiferromagnet, potentially allowing its technological utilisation in advanced spintronic devices. Furthermore, its strong quasi-two-dimensional magnetic correlations, orbitally-polarized planar ligand holes, and layered superlattice design make its electronic, magnetic, and lattice configurations resemble the precursor states of superconducting cuprates and nickelates, but with an $S \rightarrow 1$ spin state instead., Comment: 41 pages, 14 figures

CHIPS (CHerenkov detectors In mine PitS) was a prototype large-scale water Cherenkov detector located in northern Minnesota. The main aim of the R&D project was to demonstrate that construction costs of neutrino oscillation detectors could be reduced by at least an order of magnitude compared to other equivalent experiments. This article presents design features of the CHIPS detector along with details of the implementation and deployment of the prototype. While issues during and after the deployment of the detector prevented data taking, a number of key concepts and designs were successfully demonstrated.

The role of wireless communications in various domains of intelligent transportation systems is significant; it is evident that dependable message exchange between nodes (cars, bikes, pedestrians, infrastructure, etc.) has to be guaranteed to fulfill the stringent requirements for future transportation systems. A precise site-specific digital twin is seen as a key enabler for the cost-effective development and validation of future vehicular communication systems. Furthermore, achieving a realistic digital twin for dependable wireless communications requires accurate measurement, modeling, and emulation of wireless communication channels. However, contemporary approaches in these domains are not efficient enough to satisfy the foreseen needs. In this position paper, we overview the current solutions, indicate their limitations, and discuss the most prospective paths for future investigation., Comment: Submitted to IEEE Intelligent Transportation Systems Magazine

Quantum materials whose atoms are arranged on a lattice of corner-sharing triangles, $\textit{i.e.}$, the kagome lattice, have recently emerged as a captivating platform for investigating exotic correlated and topological electronic phenomena. Here, we combine ultra-low temperature angle-resolved photoemission spectroscopy (ARPES) with scanning tunneling microscopy and density functional theory calculations to reveal the fascinating electronic structure of the bilayer-distorted kagome material $\textit{Ln}$Ti${_3}$Bi${_4}$, where $\textit{Ln}$ stands for Nd and Yb. Distinct from other kagome materials, $\textit{Ln}$Ti${_3}$Bi${_4}$ exhibits two-fold, rather than six-fold, symmetries, stemming from the distorted kagome lattice, which leads to a unique electronic structure. Combining experiment and theory we map out the electronic structure and discover double flat bands as well as multiple van Hove singularities (VHSs), with one VHS exhibiting higher-order characteristics near the Fermi level. Notably, in the magnetic version NdTi${_3}$Bi${_4}$, the ultra-low base temperature ARPES measurements unveil an unconventional band splitting in the band dispersions which is induced by the ferromagnetic ordering. These findings reveal the potential of bilayer-distorted kagome metals $\textit{Ln}$Ti${_3}$Bi${_4}$ as a promising platform for exploring novel emergent phases of matter at the intersection of strong correlation and magnetism.

Transition metal oxides with a wide variety of electronic and magnetic properties offer an extraordinary possibility to be a platform for developing future electronics based on unconventional quantum phenomena, for instance, the topology. The formation of topologically non-trivial states is related to crystalline symmetry, spin-orbit coupling, and magnetic ordering. Here, we demonstrate how lattice distortions and octahedral rotation in SrNbO$_3$ films induce the band topology. By employing angle-resolved photoemission spectroscopy (ARPES) and density functional theory (DFT) calculations, we verify the presence of in-phase $a^0a^0c^+$ octahedral rotation in ultra-thin SrNbO$_3$ films, which causes the formation of topologically-protected Dirac band crossings. Our study illustrates that octahedral engineering can be effectively exploited for implanting and controlling quantum topological phases in transition metal oxides., Comment: 6 pages, 4 figures

Silicon carbide (SiC) emerges as a promising ceramic material for high-temperature structural applications, especially within the aerospace sector. The utilization of SiC-based ceramic matrix composites (CMCs) instead of superalloys in components like engine shrouds, combustors, and nozzles offers notable advantages, including a 25% improvement in fuel efficiency, over 10% enhanced thrust, and the capability to withstand up to 500$^{\circ}$C higher operating temperatures. Employing a CALPHAD-reinforced multi-phase-field model, our study delves into the evolution of the SiC layer under isothermal solidification conditions. By modeling the growth of SiC between liquid Si and solid C at 1450$^{\circ}$C, we compared results with experimental microstructures and quantitatively examined the evolution of SiC thickness over time. Efficient sampling across the entire model space mitigated uncertainty in high-temperature kinetic parameters, allowing us to predict a range of growth rates and morphologies for the SiC layer. The model accounts for parameter uncertainty stemming from limited experimental knowledge and successfully predicts relevant morphologies for the system. Experimental results validated the kinetic parameters of the simulations, offering valuable insights and potential constraints on the reaction kinetics. We further explored the significance of multi-phase-field model parameters on two key outputs, and found that the diffusion coefficient of liquid Si emerges as the most crucial parameter significantly impacting the SiC average layer thickness and grain count over time. This study provides valuable insights into the microstructure evolution of the Si-C binary system, offering pertinent information for the engineering of CMCs in industrial applications.

Superlattices of correlated oxides have been used to explore interfacial effects and to achieve additional control over the physical properties of individual constituents. In this work, we present a first-principles perspective of the strain and thickness effects in La$_{2/3}$Sr$_{1/3}$MnO$_3$/YBa$_2$Cu$_3$O$_{7}$ (LSMO/YBCO) superlattices. Our findings indicate that the presence of epitaxial strain and LSMO leads to a reduction of buckling parameters of the interfacial CuO$_2$ planes, as well as the transfer of electrons from LSMO to YBCO. In addition, the change in Cu-3$d$ valence is slightly dependent on the LSMO layer thickness. More interestingly, the in-plane ferromagnetic ground state within the CuO$_2$ planes near the interface is induced due to the local moments centered at the copper atoms. These local moments are decoupled from the charge transfer and, according to our calculations, appear mainly due to the Mn $3d$-O $2p$-Cu $3d$ hybridization being restricted to the interfacial region. The induced net magnetic ordering in interfacial copper atoms may have implications in the control of the superconducting state in the LSMO/YBCO superlattices.

Clustering clients into groups that exhibit relatively homogeneous data distributions represents one of the major means of improving the performance of federated learning (FL) in non-independent and identically distributed (non-IID) data settings. Yet, the applicability of current state-of-the-art approaches remains limited as these approaches cluster clients based on information, such as the evolution of local model parameters, that is only obtainable through actual on-client training. On the other hand, there is a need to make FL models available to clients who are not able to perform the training themselves, as they do not have the processing capabilities required for training, or simply want to use the model without participating in the training. Furthermore, the existing alternative approaches that avert the training still require that individual clients have a sufficient amount of labeled data upon which the clustering is based, essentially assuming that each client is a data annotator. In this paper, we present REPA, an approach to client clustering in non-IID FL settings that requires neither training nor labeled data collection. REPA uses a novel supervised autoencoder-based method to create embeddings that profile a client's underlying data-generating processes without exposing the data to the server and without requiring local training. Our experimental analysis over three different datasets demonstrates that REPA delivers state-of-the-art model performance while expanding the applicability of cluster-based FL to previously uncovered use cases.

We study the temperature evolution of quasiparticles in the correlated metal Sr$_2$RuO$_4$. Our angle resolved photoemission data show that quasiparticles persist up to temperatures above 200~K, far beyond the Fermi liquid regime. Extracting the quasiparticle self-energy we demonstrate that the quasiparticle residue $Z$ increases with increasing temperature. Quasiparticles eventually disappear on approaching the bad metal state of Sr$_2$RuO$_4$ not by losing weight but via excessive broadening from super-Planckian scattering. We further show that the Fermi surface of Sr$_2$RuO$_4$ - defined as the loci where the spectral function peaks - deflates with increasing temperature. These findings are in semi-quantitative agreement with dynamical mean field theory calculations., Comment: Supplemental Material available upon request

Analysis and modeling of wireless communication systems are dependent on the validity of the wide-sense stationarity uncorrelated scattering (WSSUS) assumption. However, in high-mobility scenarios, the WSSUS assumption is approximately fulfilled just over a short time period. This paper focuses on the stationarity evaluation of high-mobility multi-band channels. We evaluate the stationarity time, the time over which WSSUS is fulfilled approximately. The investigation is performed over real, measured high-mobility channels for two frequency bands, 2.55 and 25.5 GHz. Furthermore, we demonstrate the influence of the user velocity on the stationarity time. We show that the stationarity time decreases with increased relative velocity between the transmitter and the receiver. Furthermore, we show the similarity of the stationarity regions between sub-6 GHz and mmWave channels. Finally, we demonstrate that the sub-6 GHz channels are characterized by longer stationarity time., Comment: Published fpr the XXXVth URSI General Assembly and Scientific Symposium (URSI GASS 2023)

Strontium niobate has triggered a lot of interest as a transparent conductor and as a possible realization of a correlated Dirac semi-metal. Using the lattice parameters as a tunable knob, the energy landscape of octahedral tilting was mapped using density functional theory calculations. We find that biaxial compressive strain induces tilting around the out-of-plane axis, while tensile strain induces tilting around the two in-plane axes. The two competing distorted structures for compressive strain show semi-Dirac dispersions above the Fermi level in their electronic structure. Our density functional theory calculations combined with dynamical mean field theory (DFT+DMFT) reveals that dynamical correlations downshift these semi-Dirac like cones towards the Fermi energy. More generally, our study reveals that the competition between the in-phase and out-of-phase tilting in SrNbO$_3$ provides a new degree of freedom which allows for tuning the thermoelectric and optical properties. We show how the tilt angle and mode is reflected in the behavior of the Seebeck coefficient and the plasma frequency, due to changes in the band structure.

Electronic nematicity that spontaneously breaks rotational symmetry has been shown as a generic phenomenon in correlated quantum systems including high-temperature superconductors and the AV3Sb5 (A = K, Rb, Cs) family with a kagome network. Identifying the driving force has been a central challenge for understanding nematicity. In iron-based superconductors, the problem is complicated because the spin, orbital and lattice degrees of freedom are intimately coupled. In vanadium-based kagome superconductors AV3Sb5, the electronic nematicity exhibits an intriguing entanglement with the charge density wave order (CDW), making understanding its origin difficult. Recently, a new family of titanium-based kagome superconductors ATi3Bi5 has been synthesized. In sharp contrast to its vanadium-based counterpart, the electronic nematicity occurs in the absence of CDW. ATi3Bi5 provides a new window to explore the mechanism of electronic nematicity and its interplay with the orbital degree of freedom. Here, we combine polarization-dependent angle-resolved photoemission spectroscopy with density functional theory to directly reveal the band topology and orbital characters of the multi-orbital RbTi3Bi5. The promising coexistence of flat bands, type-II Dirac nodal line and nontrivial Z2 topological states is identified in RbTi3Bi5. Remarkably, our study clearly unveils the orbital character change along the G-M and G-K directions, implying a strong intrinsic inter-orbital coupling in the Ti-based kagome metals, reminiscent of iron-based superconductors. Furthermore, doping-dependent measurements directly uncover the orbital-selective features in the kagome bands, which can be well explained by the d-p hybridization. The suggested d-p hybridization, in collaboration with the inter-orbital coupling, could account for the electronic nematicity in ATi3Bi5.

The energy transition potentially poses an existential risk for major international oil companies (IOCs) if they fail to adapt to low-carbon business models. Projections of energy futures, however, are met with diverging assumptions on its scale and pace, causing disagreement among IOC decision-makers and their stakeholders over what the business model of an incumbent fossil fuel company should be. In this work, we used deep multi-agent reinforcement learning to solve an energy systems wargame wherein players simulate IOC decision-making, including hydrocarbon and low-carbon investments decisions, dividend policies, and capital structure measures, through an uncertain energy transition to explore critical and non-linear governance questions, from leveraged transitions to reserve replacements. Adversarial play facilitated by state-of-the-art algorithms revealed decision-making strategies robust to energy transition uncertainty and against multiple IOCs. In all games, robust strategies emerged in the form of low-carbon business models as a result of early transition-oriented movement. IOCs adopting such strategies outperformed business-as-usual and delayed transition strategies regardless of hydrocarbon demand projections. In addition to maximizing value, these strategies benefit greater society by contributing substantial amounts of capital necessary to accelerate the global low-carbon energy transition. Our findings point towards the need for lenders and investors to effectively mobilize transition-oriented finance and engage with IOCs to ensure responsible reallocation of capital towards low-carbon business models that would enable the emergence of fossil fuel incumbents as future low-carbon leaders.

Due to high mobility in multipath propagation environments, vehicle-to-vehicle (V2V) channels are generally time and frequency variant. Therefore, the criteria for wide-sense stationarity (WSS) and uncorrelated scattering (US) are just satisfied over very limited intervals in the time and frequency domains, respectively. We test the validity of these criteria in measured vehicular 60 GHz millimeter wave (mmWave) channels, by estimating the local scattering functions (LSFs) from the measured data. Based on the variation of the LSFs, we define time-frequency stationarity regions, over which the WSSUS assumption is assumed to be fulfilled approximately. We analyze and compare both line-of-sight (LOS) and non-LOS (NLOS) V2V communication conditions. We observe large stationarity regions for channels with a dominant LOS connection, without relative movement between the transmitting and receiving vehicle. In the same measured urban driving scenario, modified by eliminating the LOS component in the post-processing, the channel is dominated by specular components reflected from an overpassing vehicle with a relative velocity of 56 km/h. Here, we observe a stationarity bandwidth of 270 MHz. Furthermore, the NLOS channel, dominated by a single strong specular component, shows a relatively large average stationarity time of 16 ms, while the stationarity time for the channel with a rich multipath profile is much shorter, in the order of 5 ms., Comment: Accepted at Asilomar Conference on Signals, Systems, and Computers 2022, 5 pages

Regular abelian semigroups are isomorphic to a direct product of an abelian group and a rectangular band (Warne, 1994). Seeking for a similar result for nilpotency, solvability and supernilpotency of regular semigroups, we obtain that analogous statement is true only in orthodox semigroups. We provide an example that shows that the same does not have to be true in regular semigroups that are not orthodox.

Recent development in angle-resolved photoemission spectroscopy (ARPES) technique involves spatially resolving samples while maintaining the high-resolution feature of momentum space. This development easily expands the data size and its complexity for data analysis, where one of it is to label similar dispersion cuts and map them spatially. In this work, we demonstrate that the recent development in representational learning (self-supervised learning) model combined with k-means clustering can help automate that part of data analysis and save precious time, albeit with low performance. Finally, we introduce a few-shot learning (k-nearest neighbour or kNN) in representational space where we selectively choose one (k=1) image reference for each known label and subsequently label the rest of the data with respect to the nearest reference image. This last approach demonstrates the strength of the self-supervised learning to automate the image analysis in ARPES in particular and can be generalized into any science data analysis that heavily involves image data.

The Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) will detect an unprecedentedly large sample of actively accreting supermassive black holes with typical accretion disk (AD) sizes of a few light days. This brings us to face challenges in the reverberation mapping (RM) measurement of AD sizes in active galactic nuclei (AGNs) using interband continuum delays. We examine the effect of LSST cadence strategies on AD RM using our metric AGNTimeLagMetric. It accounts for redshift, cadence, the magnitude limit, and magnitude corrections for dust extinction. Running our metric on different LSST cadence strategies, we produce an atlas of the performance estimations for LSST photometric RM measurements. We provide an upper limit on the estimated number of quasars for which the AD time lag can be computed within 01000 sources in each Deep Drilling field (DDF, 10 sq. deg) in any filter, with the redshift distribution of these sources peaking at z~1. We find the LSST observation strategies with a good cadence (~ 5 days) and a long cumulative season (~9 yr), as proposed for LSST DDF, are favored for the AD size measurement. We create synthetic LSST light curves for the most suitable DDF cadences and determine RM time lags to demonstrate the impact of the best cadences based on the proposed metric., Comment: accepted for publication in the Astrophysical Journal Focus Issue on Rubin LSST cadence and survey strategy

Developing reliable methods for modulating the electronic structure of the two-dimensional electron gas (2DEG) in SrTiO3 is crucial for utilizing its full potential and inducing novel properties. Here, we show that relatively simple surface preparation reconstructs the 2DEG of SrTiO3 (STO) surface, leading to a Lifshitz-like transition. Combining experimental methods, such as angle-resolved photoemission spectroscopy (ARPES) and X-ray photoemission spectroscopy (XPS) with ab initio calculations, we find that the modulation of the surface band structures is primarily attributed to the reorganization of the chemical composition. In addition, ARPES experiments demonstrate that vacuum ultraviolet (VUV) light can be efficiently employed to alter the band renormalization of the 2DEG system and control the electron-phonon interaction (EPI). Our study provides a robust and straightforward route to stabilize and tune the low-dimensional electronic structure via the chemical degeneracy of the STO surface.